Application of ANFIS for modeling of microhardness of high strength low alloy (HSLA) steels in continuous cooling

Materials Research

Gholamreza Khalaj¹  Ali Nazari²  Akbar Karimi Livary² 

[1] ,Islamic Azad University Department of Materials Engineering, Saveh Branch Saveh,Iran

关键词: adaptive network -based fuzzy inference systems (ANFIS);    microalloyed steel;    continuous cooling;    HSLA steel;   

DOI  :  10.1590/S1516-14392013005000052

来源: SciELO

【 摘 要 】

The paper presents some results of the research connected with the development of new approach based on the Adaptive Network-based Fuzzy Inference Systems (ANFIS) of predicting the Vickers microhardness of the phase constituents occurring in five steel samples after continuous cooling. The independent variables in the model are chemical compositions, initial austenite grain size and cooling rate over the temperature range of the occurrence of phase transformations. To construct these models, 114 different experimental data were gathered from the literature. The data used in the ANFIS model is arranged in a format of twelve input parameters that cover the chemical compositions, initial austenite grain size and cooling rate, and output parameter which is Vickers microhardness. In this model, the training and testing results in the ANFIS systems have shown strong potential for prediction of effects of chemical compositions and heat treatments on hardness of microalloyed steels.

【 授权许可】

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